IDEAS home Printed from https://ideas.repec.org/a/taf/tstfxx/v3y2019i2p114-128.html
   My bibliography  Save this article

Small area prediction of quantiles for zero-inflated data and an informative sample design

Author

Listed:
  • Emily Berg
  • Danhyang Lee

Abstract

The Conservation Effects Assessment Project (CEAP) is a survey intended to quantify soil and nutrient loss on cropland. Estimates of the quantiles of CEAP response variables are published. Previous work develops a procedure for predicting small area quantiles based on a mixed effects quantile regression model. The conditional density function of the response given covariates and area random effects is approximated with the linearly interpolated generalised Pareto distribution (LIGPD). Empirical Bayes is used for prediction and a parametric bootstrap procedure is developed for mean squared error estimation. In this work, we develop two extensions of the LIGPD-based small area quantile prediction procedure. One extension allows for zero-inflated data. The second extension accounts for an informative sample design. We apply the procedures to predict quantiles of the distribution of percolation (a CEAP response variable) in Kansas counties.

Suggested Citation

  • Emily Berg & Danhyang Lee, 2019. "Small area prediction of quantiles for zero-inflated data and an informative sample design," Statistical Theory and Related Fields, Taylor & Francis Journals, vol. 3(2), pages 114-128, July.
    • Handle: RePEc:taf:tstfxx:v:3:y:2019:i:2:p:114-128
    DOI: 10.1080/24754269.2019.1666243
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/24754269.2019.1666243
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/24754269.2019.1666243?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tstfxx:v:3:y:2019:i:2:p:114-128. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tstf .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.